Journal article
Mean-variance portfolio selection with non-linear wealth dynamics and random coefficients
- Abstract:
- This paper studies the continuous time mean-variance portfolio selection problem with one kind of non-linear wealth dynamics. To deal with the expectation constraint, an auxiliary stochastic control problem is firstly solved by two new generalized stochastic Riccati equations from which a candidate portfolio in feedback form is constructed, and the corresponding wealth process will never cross the vertex of the parabola. In order to verify the optimality of the candidate portfolio, the convex duality (requires the monotonicity of the cost function) is established to give another more direct expression of the terminal wealth level. The variance-optimal martingale measure and the link between the non-linear financial market and the classical linear market are also provided. Finally, we obtain the efficient frontier in closed form. From our results, people are more likely to invest their money in riskless asset compared with the classical linear market.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 682.4KB, Terms of use)
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- Publisher copy:
- 10.1051/cocv/2024033
Authors
+ National Key R&D Program of China
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- Funder identifier:
- https://ror.org/027s68j25
- Grant:
- 2023YFA1008701
+ National Natural Science Foundation of China
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- Funder identifier:
- https://ror.org/01h0zpd94
- Grant:
- 12326332
- 11801315
+ Shandong University of Finance and Economics
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- Funder identifier:
- https://ror.org/02e2nnq08
+ Natural Science Foundation of Shandong Province
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- Grant:
- ZR2018QA001
- ZR2020MA032
- Publisher:
- EDP Sciences
- Journal:
- ESAIM: Control, Optimisation and Calculus of Variations More from this journal
- Volume:
- 30
- Article number:
- 45
- Publication date:
- 2024-06-04
- Acceptance date:
- 2024-04-09
- DOI:
- EISSN:
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1262-3377
- ISSN:
-
1292-8119
- Language:
-
English
- Keywords:
- Pubs id:
-
2008494
- UUID:
-
uuid_4412baee-e706-4fc3-98b4-8f268af9aac1
- Local pid:
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pubs:2008494
- Source identifiers:
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W4394728450
- Deposit date:
-
2026-01-21
- ARK identifier:
Terms of use
- Copyright holder:
- Ji et al.
- Copyright date:
- 2024
- Rights statement:
- © The authors. Published by EDP Sciences, SMAI 2024. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
- Licence:
- CC Attribution (CC BY)
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